Quantitative Study of Individual Emotional States in Social Networks

@article{Tang2012QuantitativeSO,
  title={Quantitative Study of Individual Emotional States in Social Networks},
  author={Jie Tang and Yuan Zhang and Jimeng Sun and Jinghai Rao and Wenjing Yu and Yiran Chen and Alvis Cheuk M. Fong},
  journal={IEEE Transactions on Affective Computing},
  year={2012},
  volume={3},
  pages={132-144}
}
  • Jie TangYuan Zhang A. Fong
  • Published 1 April 2012
  • Computer Science
  • IEEE Transactions on Affective Computing
Marketing strategies without emotion will not work. Emotion stimulates the mind 3,000 times quicker than rational thought. Such emotion invokes either a positive or a negative response and physical expressions. Understanding the underlying dynamics of users' emotions can efficiently help companies formulate marketing strategies and support after-sale services. While prior work has focused mainly on qualitative aspects, in this paper we present our research on quantitative analysis of how an… 

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References

SHOWING 1-10 OF 43 REFERENCES

MoodCast: Emotion Prediction via Dynamic Continuous Factor Graph Model

This work proposes a Mood Cast method based on a dynamic continuous factor graph model for modeling and predicting users’ emotions in a social network and shows that it can accurately predict emotion status of more than 62% of users and 8+% improvement than the baseline methods.

Twitter mood predicts the stock market

Predicting positive and negative links in online social networks

These models provide insight into some of the fundamental principles that drive the formation of signed links in networks, shedding light on theories of balance and status from social psychology and suggest social computing applications by which the attitude of one user toward another can be estimated from evidence provided by their relationships with other members of the surrounding social network.

Dynamic spread of happiness in a large social network: longitudinal analysis over 20 years in the Framingham Heart Study

People’s happiness depends on the happiness of others with whom they are connected, providing further justification for seeing happiness, like health, as a collective phenomenon.

Influence and correlation in social networks

Two simple tests are proposed that can identify influence as a source of social correlation when the time series of user actions is available and are applied to real tagging data on Flickr, exhibiting that while there is significant social correlation in tagging behavior on this system, this correlation cannot be attributed to social influence.

Situating Social Influence Processes: Dynamic, Multidirectional Flows of Influence Within Social Networks

This article reviews models of social influence from a number of fields, categorizing them using four conceptual dimensions to delineate the universe of possible models and encourages interdisciplinary collaborations to build models that incorporate the detailed, microlevel understanding of influence processes derived from focused laboratory studies but contextualized in ways that recognize how multidirectional, dynamic influences are situated in people's social networks and relationships.

Yes, there is a correlation: - from social networks to personal behavior on the web

Data mining techniques are applied to study the relationship that exists between a person's social group and his/her personal behavior for a population of over 10 million people, by turning to online sources of data.

Cooperative behavior cascades in human social networks

This work exploits a seminal set of laboratory experiments that originally showed that voluntary costly punishment can help sustain cooperation to show experimentally that cooperative behavior cascades in human social networks.

Social action tracking via noise tolerant time-varying factor graphs

Experimental results show that the proposed method outperforms several baseline methods for action prediction, and Qualitatively, the model can uncover some interesting patterns of the social dynamics.

A Critical Analysis of Rational & Emotional Approaches in Car Selling

Investment in a Car is the costliest investment made in a life time only next to construction of a house, for any human being. It is a common knowledge that all of us are attracted towards cars right